Update README.md

README.md

@@ -18,7 +18,7 @@ size_categories:
 
 
 # Summary
-This is the dataset proposed in the paper "[**OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation**](https://arxiv.org/abs/2407.02371)". 
+This is the extent dataset proposed in the paper "[**OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation**](https://arxiv.org/abs/2407.02371)". 
 OpenVid-1M is a high-quality text-to-video dataset designed for research institutions to enhance video quality, featuring high aesthetics, clarity, and resolution. It can be used for direct training or as a quality tuning complement to other video datasets.
 
 **New Feature**: Video-ZIP mapping files now available for efficient video lookup (see [Dataset Structure](#dataset-structure) and [Extended Usage](#extended-usage)).
@@ -79,8 +79,18 @@ print(f"Video {video_name} is in {result.zip_file.values[0]} at path {result.vid
 unzip OpenVid_part0.zip "OpenVid_part1/celebv_--Jiv5iYqT8_0.mp4" -d target_folder
 # Unzip files (-j flattens directory structure)
 ```
+# Citation and Acknowledgments
+
+This mapping dataset was developed to enhance **OpenVid-1M** accessibility. Special thanks to the original dataset contributors.
+
+```bibtex
+@article{nan2024openvid,
+  title={OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation},
+  author={Nan, Kepan and Xie, Rui and Zhou, Penghao and Fan, Tiehan and Yang, Zhenheng and Chen, Zhijie and Li, Xiang and Yang, Jian and Tai, Ying},
+  journal={arXiv preprint arXiv:2407.02371},
+  year={2024}
+}
+```
 
 
 
-# Acknowledgments
-The video-ZIP mapping system was developed to enhance dataset accessibility while maintaining original directory structures. Special thanks to the original dataset contributors.